Although spatial studies of diseases on land have a long history, far fewer have been made on aquatic diseases. Here, we present the first large-scale, high-resolution spatial and temporal representation of a mass mortality phenomenon cause by the Ostreid herpesvirus (OsHV-1) that has affected oysters (Crassostrea gigas) every year since 2008, in relation to their energetic reserves and the quality of their food. Disease mortality was investigated in healthy oysters deployed at 106 locations in the Thau Mediterranean lagoon before the start of the epizootic in spring 2011. We found that disease mortality of oysters showed strong spatial dependence clearly reflecting the epizootic process of local transmission. Disease initiated inside oyster farms spread rapidly beyond these areas. Local differences in energetic condition of oysters, partly driven by variation in food quality, played a significant role in the spatial and temporal dynamics of disease mortality. In particular, the relative contribution of diatoms to the diet of oysters was positively correlated with their energetic reserves, which in turn decreased the risk of disease mortality.

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Nowadays, geostatistics is commonly applied for numerous gridding or modelling tasks. However, it is still under used and unknown for classical geophysical applications. This paper highlights the main geostatistical methods relevant for geophysical issues, for instance to improve the quality of seismic data such as velocity cubes or interpreted horizons. These methods are then illustrated through four examples. The first example, based on a gravity survey presents how a geostatistical interpolation can be used to filter out a global trend, in order to better define real anomalies. In the second case study, dedicated to refraction surveying, geostatistical filtering is used to filter out acquisition artefacts and identify the main geological structures. The third one is an example of porosity being integrated geostatistically with a seismic acoustic impedance map. The last example deals with geostatistical time to depth conversion; the interest of performing geostatistical simulations is finally discussed.

[1] This paper presents a flexible and general methodology that combines hydrogeological and geostatistical modeling techniques to estimate a set of transmissivity fields and their influence on flow and transport. The methodology may be applied to any case with only hydraulic head observations, even if most of them are concentrated inside a small part of the entire domain of interest. It is applied here to the case of the Champagne chalk aquifer (France), where it is shown to be very efficient. The methodology is decomposed in three independent parts. First, a reference head distribution is constructed by kriging in order to constrain the inverse problem. As hydraulic heads and elevations are correlated, a smoothed digital elevation model is used as external drift. The inverse problem is then solved by using a simplified pilot point method with an efficient and easy-to-use minimization algorithm. Finally, geostatistical simulations combined with flow simulations lead to a set of acceptable transmissivity fields. The induced uncertainty is evaluated by calculating tracer concentrations, pointing out areas where flow behavior is uncertain and where new borings would be advantageously drilled.

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